Life tables adjusted for comorbidity more accurately estimate noncancer survival for recently diagnosed cancer patients

J Clin Epidemiol. 2013 Dec;66(12):1376-85. doi: 10.1016/j.jclinepi.2013.07.002. Epub 2013 Sep 10.


Objectives: To provide cancer patients and clinicians with more accurate estimates of a patient's life expectancy with respect to noncancer mortality, we estimated comorbidity-adjusted life tables and health-adjusted age.

Study design and setting: Using data from the Surveillance Epidemiology and End Results-Medicare database, we estimated comorbidity scores that reflect the health status of people who are 66 years of age and older in the year before cancer diagnosis. Noncancer survival by comorbidity score was estimated for each age, race, and sex. Health-adjusted age was estimated by systematically comparing the noncancer survival models with US life tables.

Results: Comorbidity, cancer status, sex, and race are all important predictors of noncancer survival; however, their relative impact on noncancer survival decreases as age increases. Survival models by comorbidity better predicted noncancer survival than the US life tables. The health-adjusted age and national life tables can be consulted to provide an approximate estimate of a person's life expectancy, for example, the health-adjusted age of a black man aged 75 years with no comorbidities is 67 years, giving him a life expectancy of 13 years.

Conclusion: The health-adjusted age and the life tables adjusted by age, race, sex, and comorbidity can provide important information to facilitate decision making about treatment for cancer and other conditions.

Keywords: Cancer; Comorbidity; Health-adjusted age; Life expectancy; Life tables; SEER–Medicare; Survival.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Comorbidity*
  • Female
  • Humans
  • Life Expectancy* / ethnology
  • Life Tables*
  • Male
  • Neoplasms / diagnosis
  • Neoplasms / epidemiology*
  • Racial Groups / statistics & numerical data
  • Reproducibility of Results
  • SEER Program
  • Survival Analysis
  • United States / epidemiology